Managing physical resources for virtual network functions

ABSTRACT

A method includes receiving profile information for a network. The method also includes determining a network configuration based on at least a constraint associated with at least one of a network session or a hardware capacity of a hardware platform of the network and a number of sessions that the network configured based on the network configuration can support. The method also includes configuring the network based on the network configuration.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims priority to,application Ser. No. 15/363,511, entitled “Managing Physical Resourcesfor Virtual Network Functions” and filed Nov. 29, 2016, the entirety ofwhich is hereby incorporated by reference.

TECHNICAL FIELD

This disclosure relates generally to network management and, morespecifically, to network design and capacity planning.

BACKGROUND

To provide a service using virtualized network platforms, a set ofvirtual network functions (VNFs) may be instantiated on general purposehardware. Each VNF may require one or more virtual machines (VMs) to beinstantiated. In turn, VMs may require various resources, such asmemory, virtual computer processing units (vCPUs), and networkinterfaces or network interface cards (NICs). Determining how to assignthese resources among VMs in an efficient manner may be unbearablycomplex.

This disclosure is directed to solving one or more of the problems inthe existing technology.

SUMMARY

In an aspect, a method may include receiving profile information for anetwork. The method may also include determining a network configurationbased on at least a constraint associated with at least one of a networksession or a hardware capacity of a hardware platform of the network anda number of sessions that the network configured based on the networkconfiguration can support. The method may also include configuring thenetwork based on the network configuration.

In another aspect, a method may include receiving profile informationfor a network. The method may also include determining constraintsassociated with at least one of a network session or a hardware capacityof a hardware platform of the network and determining configurations ofthe network based on the profile information and the constraints. Themethod may also include identifying a subset of the configurations thatsatisfies an anti-affinity rule associated with a virtual resource to beused to implement the network session and identifying a networkconfiguration of the subset that supports a greater number of sessionsthan another configuration of the subset. The method may also includeconfiguring the network based on the network configuration to supportthe greater number of sessions. The network configuration may assign atleast one instantiation of a virtual machine (VM) of a first VM type forat least one instantiation of a virtual network function (VNF) of afirst VNF type to at least one server of the hardware platform.

According to yet another aspect, a system may include an input/outputcommunicatively coupled to a—network and a processor. The system mayalso include memory that stores instructions that may cause theprocessor executing the instructions to effectuate operations. Theoperations may include receiving, via the input/output, profileinformation for the network. The operations may also include determiningconstraints associated with at least one of a network session or ahardware capacity of a hardware platform of the network and determiningconfigurations of the network based on the profile information and theconstraints. The operations may also include identifying a subset of theconfigurations that satisfies an anti-affinity rule associated with avirtual resource to be used to implement the network session. Theoperations may also include identifying a network configuration of thesubset that supports a greater number of sessions than anotherconfiguration of the subset and sending a command via the input/outputto the network. The command may cause the network to be configured basedon the network configuration.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide an understanding ofthe variations in implementing the disclosed technology. However, theinstant disclosure may take many different forms and should not beconstrued as limited to the examples set forth herein. Where practical,like numbers refer to like elements throughout.

FIG. 1A is a representation of an exemplary network.

FIG. 1B is a representation of an exemplary hardware platform for anetwork.

FIG. 2A illustrates a data flow for a system that may be used forconfiguring a virtualized network platform.

FIG. 2B is a method that may be used for configuring a virtualizednetwork platform.

FIG. 3 is a schematic of an exemplary device that may be a component ofthe system of FIG. 2A.

FIG. 4 depicts an exemplary communication system that provide wirelesstelecommunication services over wireless communication networks that maybe modeled using the disclosed systems and methods for configuring avirtualized network platform.

FIG. 5 depicts an exemplary communication system that provide wirelesstelecommunication services over wireless communication networks that maybe modeled using the disclosed systems and methods for configuring avirtualized network platform.

FIG. 6 is a diagram of an exemplary telecommunications system in whichthe disclosed methods and processes may be implemented.

FIG. 7 is an example system diagram of a radio access network and a corenetwork that may be modeled using the disclosed systems and methods forconfiguring a virtualized network platform.

DETAILED DESCRIPTION

FIG. 1A is a representation of an exemplary network 100. Network 100 mayinclude one or more virtualized functions implemented on general purposehardware, such as in lieu of having dedicated hardware for every networkfunction. That is, general purpose hardware of network 100 may beconfigured to run virtual network elements to support communicationservices, such as mobility services, including consumer services andenterprise services. These services may be provided or measured insessions.

A virtual network functions (VNFs) 102 may be able to support a limitednumber of sessions. Each VNF 102 may have a VNF type that indicates itsfunctionality or role. For example, FIG. 1A illustrates a gateway VNF102 a and a policy and charging rules function (PCRF) VNF 102 b.Additionally or alternatively, VNFs 102 may include other types of VNFs.Each VNF 102 may use one or more virtual machines (VMs) 104 to operate.Each VM 104 may have a VM type that indicates its functionality or role.For example, FIG. 1A illustrates a MCM VM 104 a, an ASM VM 104 b, and aDEP VM 104 c. Additionally or alternatively, VMs 104 may include othertypes of VMs. Each VM 104 may consume various network resources from ahardware platform 106, such as a resource 108, a virtual centralprocessing unit (vCPU) 108 a, memory 108 b, or a network interface card(NIC) 108 c. Additionally or alternatively, hardware platform 106 mayinclude other types of resources 108.

While FIG. 1A illustrates resources 108 as collectively contained inhardware platform 106, the configuration of hardware platform 106 mayisolate, for example, certain memory 108 b from other memory 108 b. FIG.1B provides an exemplary implementation of hardware platform 106.

Hardware platform 106 may comprise one or more chasses 110. Chassis 110may refer to the physical housing or platform for multiple servers orother network equipment. In an aspect, chassis 110 may also refer to theunderlying network equipment. Chassis 110 may include one or moreservers 112. Server 112 may comprise general purpose computer hardwareor a computer. In an aspect, chassis 110 may comprise a metal rack, andservers 112 of chassis 110 may comprise blade servers that arephysically mounted in or on chassis 110.

Each server 112 may include one or more network resources 108, asillustrated. Servers 112 may be communicatively coupled together (notshown) in any combination or arrangement. For example, all servers 112within a given chassis 110 may be communicatively coupled. As anotherexample, servers 112 in different chasses 110 may be communicativelycoupled. Additionally or alternatively, chasses 110 may becommunicatively coupled together (not shown) in any combination orarrangement.

The characteristics of each chassis 110 and each server 112 may differ.For example, FIG. 1B illustrates that the number of servers 112 withintwo chasses 110 may vary. Additionally or alternatively, the type ornumber of resources 108 within each server 112 may vary. In an aspect,chassis 110 may be used to group servers 112 with the same resourcecharacteristics. In another aspect, servers 112 within the same chassis110 may have different resource characteristics.

Given hardware platform 106, the number of sessions that may beinstantiated may vary depending upon how efficiently resources 108 areassigned to different VMs 104. For example, assignment of VMs 104 toparticular resources 108 may be constrained by one or more rules. Forexample, these rules may include one or more affinity rules oranti-affinity rules.

An affinity rule may restrict assignment of resources 108 for aparticular VM 104 (or a particular type of VM 104). For example, anaffinity rule may require that certain VMs 104 be instantiated on (thatis, consume resources from) the same server 112 or chassis 110. Forexample, an affinity rule may require that resources 108 assigned to aparticular VM 104 be on the same server 112 or set of servers 112. Forexample, if VM 104 uses eight vCPUs 108 a, one GB of memory 108 b, andtwo NICs 108 c, the rules may require that all of these resources 108 besourced from the same server 112. For example, if VNF 102 uses six MCMVMs 104 a, an affinity rule may dictate that those six MCM VMs 104 a beinstantiated on the same server 112 (or chassis 110). As anotherexample, if VNF 102 uses MCM VMs 104 a, ASM VMs 104 b, and a third typeof VMs 104, an affinity rule may dictate that at least the MCM VMs 104 aand the ASM VMs 104 b be instantiated on the same server 112 (or chassis110). Affinity rules may restrict assignment of resources 108 based onthe identity or type of resource 108, VNF 102, VM 104, chassis 110,server 112, or any combination thereof.

An anti-affinity rule may restrict assignment of resources 108 for aparticular VM 104 (or a particular type of VM 104). In contrast to anaffinity rule—which may require that certain VMs 104 be instantiated onthe same server 112 or chassis 110—an anti-affinity rule requires thatcertain VMs 104 be instantiated on different servers 112 (or differentchasses 110). For example, an anti-affinity rule may require that MCM VM104 a be instantiated on a particular server 112 that does not containany ASM VMs 104 b. As another example, an anti-affinity rule may requirethat MCM VMs 104 a for a first VNF 102 be instantiated on a differentserver 112 (or chassis 110) than MCM VMs 104 a for a second VNF 102.Anti-affinity rules may restrict assignment of resources 108 based onthe identity or type of resource 108, VNF 102, VM 104, chassis 110,server 112, or any combination thereof.

Within these constraints, resources 108 of hardware platform 106 may beassigned to be used to instantiate VMs 104, which in turn may be used toinstantiate VNFs 102, which in turn may be used to establish sessions.The different combinations for how such resources 108 may be assignedmay vary in complexity and efficiency. For example, differentassignments may have different limits of the number of sessions that canbe established given a particular hardware platform 106.

For example, consider a session that may require gateway VNF 102 a andPCRF VNF 102 b. Gateway VNF 102 a may require five VMs 104 instantiatedon the same server 112, and PCRF VNF 102 b may require two VMs 104instantiated on the same server 112. (For this example, assume that noaffinity or anti-affinity rules restrict whether VMs 104 for PCRF VNF102 b may or must be instantiated on the same or different server 112than VMs 104 for gateway VNF 102 a.) In this example, each of twoservers 112 may have sufficient resources 108 to support 10 VMs 104. Ina first configuration, to implement sessions using these two servers112, first server 112 may be instantiated with 10 VMs 104 to support twoinstantiations of gateway VNF 102 a, and second server 112 may beinstantiated with 9 VMs: five VMs 104 to support one instantiation ofgateway VNF 102 a and four VMs 104 to support two instantiations of PCRFVNF 102 b. This may leave the remaining resources 108 that could havesupported the tenth VM 104 on second server 112 unused (and unusable foran instantiation of either a gateway VNF 102 a or a PCRF VNF 102 b).Alternatively, in a second configuration, first server 112 may beinstantiated with 10 VMs 104 for two instantiations of gateway VNF 102 aand second server 112 may be instantiated with 10 VMs 104 for fiveinstantiations of PCRF VNF 102 b, using all available resources 108 tomaximize the number of VMs 104 instantiated. By looking only at whichconfiguration makes use of all available resources, it would appear thatthe second configuration would be more preferable.

Consider, further, how many sessions each gateway VNF 102 a and eachPCRF VNF 102 b may support. These session capacities may factor intowhich assignment of resources 108 is more efficient. For example,consider if each gateway VNF 102 a supports two million sessions, and ifeach PCRF VNF 102 b supports three million sessions. For the firstconfiguration—three total gateway VNFs 102 a (which satisfy the gatewayrequirement for six million sessions) and two total PCRF VNFs 102 b(which satisfy the PCRF requirement for six million sessions)—wouldsupport a total of six million sessions. For the secondconfiguration—two total gateway VNFs 102 a (which satisfy the gatewayrequirement for four million sessions) and five total PCRF VNFs 102 b(which satisfy the PCRF requirement for 15 million sessions)—wouldsupport a total of four million sessions. Thus, while the firstconfiguration may seem less efficient looking only at the number ofavailable resources 108 used (as resources 108 for the tenth possible VM104 are unused), the first configuration is actually more efficient fromthe perspective of being the configuration that can support more thegreater number of sessions. (The second configuration supports fourmillion sessions, while the first configuration supports six millionsessions.) Since the objective goal is to maximize the number ofsessions, choosing the second configuration, even though it may leaveone available VM 104 unused, may actually be preferable.

To solve the problem of determining a capacity (e.g., number ofsessions) that can be supported by a given hardware platform 105, agiven requirement for VNFs 102 to support a session, a capacity for thenumber of sessions each VNF 102 (e.g., of a certain type) can support, agiven requirement for VMs 104 for each VNF 102 (e.g., of a certaintype), a give requirement for resources 108 to support each VM 104(e.g., of a certain type), rules dictating the assignment of resources108 to one or more VMs 104 (e.g., affinity and anti-affinity rules), thechasses 110 and servers 112 of hardware platform 106, and the individualresources 108 of each chassis 110 or server 112 (e.g., of a certaintype), a formulation of an integer programming problem may be created.

In an aspect, the integer programming problem may be designed tomaximize or minimize a linear function of one or more variables. In anaspect, an integer programming problem may be constrained by one or moreinequality or equality constraints that limit the linear function. Inanother aspect, some or all of the variables may be integer valued. Inanother aspect, one or more variables may be binary.

First, a plurality of index sets may be established. For example, indexset L may include the set of chasses 110. For example, if a systemallows up to 6 chasses 110, this set may be:

L={1, 2, 3, 4, 5, 6},

where l is an element of L.

Another index set J may include the set of servers 112. For example, ifa system allows up to 16 servers 112 per chassis 110, this set may be:

J={1, 2, 3, . . . , 16},

where j is an element of J.

As another example, index set K having at least one element k mayinclude the set of VNFs 102 that may be considered. For example, thisindex set may include all types of VNFs 102 that may be used toinstantiate a service. For example, let

K={GW, PCRF}

where GW represents gateway VNFs 102 a and PCRF represents PCRF VNFs 102b.

Another index set N may include the set of possible instances of a givenVNF 102. For example, if a system allows up to 10 instances of VNF 102,this set may be:

N={1, 2, 3, . . . , 10},

where n is an element of N.

Another index set I(k) may equal the set of types of VMs 104 for a VNF102 k. Thus, let

I(GW)={MCM, ASM, IOM, WSM, CCM, DCM}

represent VMs 104 for gateway VNF 102 a, where MCM represents MCM VM 104a, ASM represents ASM VM 104 b, and each of IOM, WSM, CCM, and DCMrepresents a respective type of VM 104. Further, let

I(PCRF)={DEP, DIR, POL, SES, MAN}

represent VMs 104 for PCRF VNF 102 b, where DEP represents DEP VM 104 cand each of DIR, POL, SES, and MAN represent a respective type of VM104.

There are other ways to implement the data sets, which may be used informulations of the integer programming problem. For example, a set KImay have members that are tuples (k, i) to represent an instance andtype of VNF 102. As another example, a set LJ may have members that aretuples (l, j) to represent server 112 in chassis 110.

Another index set V may include the set of possible instances of a givenVM 104. For example, if a system allows up to 20 instances of VMs 104,this set may be:

V={1, 2, 3, . . . , 20},

where v is an element of V.

In addition to the sets, the integer programming problem may includeadditional data. The characteristics of VNFs 102, VMs 104, chasses 110,or servers 112 may be factored into the problem. This data may bereferred to as parameters. For example, for given VNF 102 k, the numberof sessions that VNF 102 k can support may be defined as a functionS(k). In an aspect, for an element k of set K,

param S(k)>0;is a measurement of the number of sessions k can support. Returning tothe earlier example where gateway VNF 102 a may support 2 millionsessions, then the data may beparam S(GW)=2,000,000.

VM 104 modularity may be another parameter in the integer programmingproblem. VM 104 modularity may represent the VM 104 requirement for atype of VNF 102. For example, for k that is an element of set K and ithat is an element of set I, each instance of VNF k may require M(k, i)instances of VMs 104. For example, recall the example where

I(GW)={MCM, ASM, IOM, WSM, CCM, DCM}.

In an example, M(GW, I(GW)) may be the set that indicates the number ofeach type of VM 104 that may be required to instantiate gateway VNF 102a. For example,

M(GW, I(GW))={2, 16, 4, 4, 2, 4}

may indicate that one instantiation of gateway VNF 102 a may require twoinstantiations of MCM VMs 104 a, 16 instantiations of ASM VM 104 b, fourinstantiations of IOM VM 104, four instantiations of WSM VM 104, twoinstantiations of CCM VM 104, and four instantiations of DCM VM 104.

Parameters may indicate the resource requirements of a given VNF 102 orVM 104. For example, in the example hardware platform 106, resources 108may include vCPUs 108 a, memory 108 b, and NICs 108 c. A parameter maybe used to indicate the requirements of these resources for a particularVNF 102. For example, the processing power (e.g., vCPU) requirement foreach VM 104 of type i for an instance of VNF 102 of type k may beimplemented as:

param Cki{K, I}>=0;As another example, the memory requirement (e.g., measured in gigabytes)for each VM 104 of type i for an instance of VNF 102 of type k may beimplemented as:param Rki{K, I}>=0;As yet another example, the connection requirement (e.g., measured innumber of NICs 108 c) for each VM 104 of type i for an instance of VNF102 of type k may be implemented as:param Eki{K, I}>=0;

Another parameter may indicate the capacity of hardware platform 106.For example, for each type of resource 108 there may be a parameter thatindicates the amount of that type of resource. For example, a parameterClj may indicate the processing power (e.g., measured by the number ofvCPUs 108 a) in one server 112 j within one chassis 110 l:

param Clj>=0;As another example, a parameter Rlj may indicate the amount of memory(e.g., measured in gigabytes) in one server 112 j within one chassis1101:param Rlj>=0;As another example, a parameter Elj may indicate the amount of networkconnections (e.g., measured in number of NICS 108 c) in one server 112 jwithin one chassis 1101:param Elj>=0;

With the data of the index sets and parameters, one or more variablesmay be defined and used for calculating the integer programming problem.For example, a binary variable X may be used to indicate whether aninstance v of VM 104 of type i for an instance n of VNF 102 of type k isinstantiated on server 112 j of chassis 110. This variable may beimplemented as:

var X {k in K, i in I, v in V, n in N, l in L, j in J} binary;and may equal true (or 1) if instance v of type i for instance n of typek is instantiated on j of l. Otherwise, X may equal false (or 0).

Another binary variable Y may be used to indicate whether an instance nof VNF 102 of type k has been instantiated. This variable may beimplemented as:

var Y {k in K, n in N} binary;and may equal true (or 1) if instance n of type k has been instantiated.Otherwise, Y may equal false (or 0).

The objective function, which may be the ultimate variable that theinteger programming problem is designed to maximize, may be establishedas variable Z. Z may be implemented as:

var Z; and the objective function may be represented as:maximize minimum demand feasible:

Z;

In this form, the objective function may be implemented or set up in analgebraic modeling language, such as AMPL.

However, given the complexity of the integer programming problem—thenumerous variables and restrictions that must be satisfied—implementingan algorithm that may be used to solve the integer programming problemefficiently, without sacrificing optimality, may be difficult. As theexamples in this disclosure suggest, there may be multiple variables,parameters, and constraints that must be considered in solving for Z. Asthe following explanation steps through the requirements of thecalculation from a mathematical standpoint, different approaches foroptimizing the implementations of such calculations are also provided.

To solve for Z, which may indicate optimized session capacity for theentire hardware platform 106, this problem may be broken down further,to the capacity for each type k of VNF 102. Thus, a variable W mayindicate the capacity of type k:

var W{k in K};

And, because hardware platform 106 cannot have a greater capacity thanany of the capacities of the individual types k of VNFs 102 that areused to establish sessions, then it can be stated that:

Z≤W(k)

for any k in K.

In turn, the capacity of type k of VNFs 102 can be expressed as aformula multiplying the capacity of a single instance of VNF 102 of typek—e.g., Ck(k)—by the total number of instances n of VNFs 102 of type k.Calculating a summation of the binary variable Y for all possibleinstances n of type k, the total number of instances n can be

${W(k)} = {{{Ck}(k)} \times {\sum\limits_{n \in N}{Y\left( {k,n} \right)}}}$

This constraint may be implemented as:

subject to W definition {k in K}:W[k]=Ck[k]*sum{n in N}Y[k, n];

Thus, in the previous example where each instance of gateway VNF 102 acan support 2 million sessions and each instance of PCRF gateway 102 bcan support 3 million sessions, if there are two instances n of each oftype of VNFs 102, then:

${{W({GW})} = {{2\text{,}000\text{,}000 \times {\sum\limits_{n \in \; N}{Y\left( {{GW},n} \right)}}} = {2\text{,}000}}},{{000 \times 2} = {4\text{,}000\text{,}000}}$${{W({PCRF})} = {{3\text{,}000\text{,}000 \times {\sum\limits_{n \in \; N}{Y\left( {{PCRF},n} \right)}}} = {3\text{,}000}}},{{000 \times 2} = {6\text{,}000\text{,}000}}$

And since Z must not be greater than any W(k), then

Z≤4,000,000

For while PCRF VNFs 102 b can support 2,000,000 sessions more, there arenot enough gateway VNFs 102 a to establish any of those additionalsessions. This constraint, that Z cannot exceed the minimum W(k), may beimplemented as:subject to Z definition{k in K}:

Z<=W[k];

Another key category of constraints is that the total number ofallocated resources 108 within server 112 should be less than themaximum amount of resources 108 within that server 112. That is, ifserver 112 only has 10 vCPUs 108 a, then no more than 10 vCPUs 108 afrom that server 112 may be allocated. For example, the processing powerallocation constraints may be represented as:

${\sum\limits_{k \in K}{\sum\limits_{i \in I}{\sum\limits_{v \in V}{\sum\limits_{n \in N}{{X\left( {k,i,v,n,l,j} \right)} \times {{Cki}\left( {k,i} \right)}}}}}} \leq {Clj}$

Then, to implement the constraint that no more vCPUs 108 a may beallocated from a given server 112 than exist in that server 112, avariable virtualCPU may be initialized to represent the total vCPUs 108a allocated to server 112 j of chassis 110 l:

var virtualCPU{l in L, j in J};Then, the equation above may be implemented as:subject to virtualCPU{(l, j) in LJ}:sum{k in K, i in I, v in V, n in N} X[k, i, v, n, l, j]*Cki[k, i]<=Clj;

While the above constraint may be technically and mathematicallycorrect, computational limits of the system running the calculations maymake it difficult to efficiently or timely obtain results. This may bein part based on the size of the search tree that is formed inperforming such calculations. Thus, different methods may be used toexpress the same equation in different manners that facilitatecalculation of the equation by a computer program.

One approach is to disaggregate the equations by breaking them up bytype of VNF K. Thus, in a scenario where K={GW, PCRF}, the equations forconfirming that no resources 108 are allocated than actually exist mayinclude (1) calculating the total resources 108 of a given type that areallocated for gateway VNFs 102 a, (2) calculating the total resources108 of a given type that are allocated for PCRF VNFs 102 b, and (3)adding the amounts calculated in (1) and (2) together, confirming thatthe sum of (1) and (2) does not exceed Clj.

By expressing these calculations separately, the size of the set fromwhich certain members are selected for each calculation may be smallerthan the size of calculating the full constraint on Clj would have been.For example, a set VGW may include only those instances v of VMs 104that are implemented for gateway VNFs 102 a (e.g., as opposed toinstances implemented for PCRF VNFs 102 b). Similarly, a set VPCRF mayinclude only those instances v of VMs 104 that are implemented for PCRFVNFs 102 b (e.g., as opposed to instances implemented for gateway VNFs102 a). For example, these sets may be implemented as:

set VGW; set VPCRF;

Thus, the above equations (1) and (2), respectively, may be rewrittenas:

${{virtualCPUgw}\left( {l,j} \right)} = {\sum\limits_{i \in I}{\sum\limits_{v \in {VGW}}{\sum\limits_{n \in N}{{X\left( {{GW},i,v,n,l,j} \right)} \times {{Cki}\left( {{GW},i} \right)}}}}}$

(2) the equation for allocated vCPUs 108 a for PCRF VNFs 104 may be:

${{virtualCPUpcrf}\left( {l,j} \right)} = {\sum\limits_{i \in I}{\sum\limits_{v \in {VPCRF}}{\sum\limits_{n \in N}{{X\left( {{PCRF},i,v,n,l,j} \right)} \times {{Cki}\left( {{PCRF},i} \right)}}}}}$

And the total restriction on allocated vCPU 108 a may be represented as:

virtualCPUgw(l,j)+virtualCPUpcrf(l,j)≤Clj

While the equation above is equal to the originally expressedconstraint:

${\sum\limits_{k \in K}{\sum\limits_{i \in I}{\sum\limits_{v \in V}{\sum\limits_{n \in N}{{X\left( {k,i,v,n,l,j} \right)} \times {{Cki}\left( {k,i} \right)}}}}}} \leq {Clj}$

by decreasing the set over which the summations for v are calculated mayresult in a noticeable decrease the processing, memory, or time requiredto calculate the equations, particularly when the size of the sets arerelatively large. That is, while the two above equations share the samemathematical complexity, they may have different computationalcosts—that is, the time, computing power, or memory of computing theformer may be less than computing the latter.

Implementing these constraints may include establishing variables thatindicate the total vCPUs 108 a allocated in server 112 of chassis 110for (1) gateway VNFs 102 a and (2) PCRF VNFs 102 b, respectively. Forexample, these may be implemented as:

var virtualCPUgw{(l, j) in LJ};var virtualCPUpcrf{(l, j) in LJ};where virtualCPU{(l, j) in LJ}=virtualCPUgw{(l, j) inLJ}+virtualCPUpcrf{(l, j) in LJ}

Thus, implementing the constraints of allocating only those existingvCPUs 108 a may be implemented as:

subject to GWvCPU{(l, j) in LJ}:virtualCPUgw[l, j]=sum{(GW, i) in KI, v in VGW, n in N} X[GW, i, v, n,l, j]*Cki[GW, i];subject to PCRFvCPU{(l, j) in LJ}:virtualCPUpcrf[l, j]=sum{(PCRF, i) in KI, v in VPCRF, n in N} X[PCRF, i,v, n, l, j]*Cki[PCRF, i];subject to virtualCPU{(l, j) in LJ}:virtualCPUgw[l, j]+virtualCPUpcrf[1, j]<=Clj

Thus, the allocation constraint for vCPU 108 a resources is calculatedas three calculations. This decreases the size of the search treewithout compromising the result.

The same methods may be used for implementing constraints that otherresources 108 within each server 112 of each chassis 110 are notover-allocated. For example, constraints to ensure that only memory 108b that actually exists within each server 112 j of chassis 110 isallocated may be represented by the equations:

${{virtualMemoryGW}\left( {l,j} \right)} = {\sum\limits_{i \in I}{\sum\limits_{v \in {VGW}}{\sum\limits_{n \in N}{{X\left( {{GW},i,v,n,l,j} \right)} \times {{Rki}\left( {{GW},i} \right)}}}}}$${{virtualMemoryPCRF}\left( {l,j} \right)} = {\sum\limits_{i \in I}{\sum\limits_{v \in {VPCRF}}{\sum\limits_{n \in N}{{X\left( {{PCRF},i,v,n,l,j} \right)} \times {{Rki}\left( {{PCRF},i} \right)}}}}}$

And the total restriction on allocated memory 108 b may be representedas:

virtualMemoryGW(l,j)+virtualMemoryPCRF(l,j)≤Rlj

These constraints may then be implemented as:

subject to GWvMemory{(l, j) in LJ}:virtualMemoryGW[l, j]=sum{(GW, i) in KI, v in VGW, n in N} X[GW, i, v,n, l, j]*Rki[GW, i];subject to PCRFvMemory{(l, j) in LJ}:virtualMemoryPCRF[l, j]=sum{(PCRF, i) in KI, v in VPCRF, n in N} X[PCRF,i, v, n, l, j]*Rki[PCRF, i];subject to virtualMemory{(l, j) in LJ}:virtualMemoryGW[l, j]+virtualMemoryPCRF[l, j]<=Rlj;

This implementation—disaggregating the allocations by type of VNF102—like the disaggregation for the vCPU 108 a allocations, may have theadvantage of the same computational efficiencies over an implementationthat does not use such disaggregation, such as:

subject to virtualMemory{(l, j) in LJ}:sum{(k, i) in KI, v in V, n in N} X[k, i, v, n, l, j]*Rki[k, i]<=Rlj;

As another example, constraints to ensure that only NICs 108 c thatactually exists within each server 112 j of chassis 110 is allocated maybe represented by the equations:

${{virtualNICgw}\left( {l,j} \right)} = {\sum\limits_{i \in I}{\sum\limits_{v \in {VGW}}{\sum\limits_{n \in N}{{X\left( {{GW},i,v,n,l,j} \right)} \times {{Eki}\left( {{GW},i} \right)}}}}}$${{virtualNICpcrf}\left( {l,j} \right)} = {\sum\limits_{i \in I}{\sum\limits_{v \in {VPCRF}}{\sum\limits_{n \in N}{{X\left( {{PCRF},i,v,n,l,j} \right)} \times {{Eki}\left( {{PCRF},i} \right)}}}}}$

And the total restriction on allocated NICs 108 c may be represented as:

virtualNICgw(l,j)+virtualNICpcrf(l,j)≤Elj

These constraints may then be implemented as:

subject to GWvNIC {(l, j) in LJ}:virtualNICgw[l, j]=sum{(GW, i) in KI, v in VGW, n in N} X[GW, i, v, n,l, j]*Eki[GW, i];subject to PCRFvNIC{(l, j) in LJ}:virtualNICpcrf[l, j]=sum{(PCRF, i) in KI, v in VPCRF, n in N} X[PCRF, i,v, n, l, j]*Eki[PCRF, i];subject to virtualNIC{(l, j) in LJ}:virtualNICgw[l, j]+virtualNICpcrf[l, j]<=Elj;

This implementation—disaggregating the allocations by type of VNF102—like the disaggregation for the vCPU 108 a allocations, may have theadvantage of the same computational efficiencies over an implementationthat does not use such disaggregation, such as:

subject to virtualNIC{(l, j) in LJ}:sum{(k, i) in KI, v in V, n in N} X[k, i, v, n, l, j]*Eki[k, i]<=Elj;

However, depending upon resource demands of the computer systemcalculating the values and the relative sizes of the search trees underdifferent implementations of these calculations, it may advantageous orpreferable to implemented the simplified, cumulative calculation in lieuof the disaggregated calculations for certain variables. Additionally oralternatively, the disaggregation may be conducted based on otherfactors besides those contained herein. For example, while the exampleabove illustrates breaking out equations for each type of VNF 102,certain implementations may disaggregate into subgroups of K (e.g., suchthat each disaggregation actually accounts for more than one type, butless than all types of VNFs 102). Additionally or alternatively,disaggregation may be conducted based on any other factors asappropriate, such as type of VM 104, type of VNF 102, type of chassis110, type of server 112, or any combination thereof. For example, theabove-drafted implementations are drafted using the assumption that eachserver 112 within each chassis 110 has the same capacity of vCPU 108 a,memory 108 b, and NIC 108 c (variables Clj, Rlj, and Elj, respectively).However, certain implementations may use varying types and sizes ofservers 112 or chassis 110, which may require or improve accuracy byimplementing multiple variables Clj, Rlj, and Elj to account for thevariances among the hardware platform 104. Thus, it may be thatimplementing these calculations could also be disaggregated based onthese or other factors.

Another constraint may require that to assign an instance n of type k ofVNF 102 to a particular server 112 of a particular chassis 110, instancen must be used. Thus, for a given server 112 and chassis 110, the sum ofthe number of VMs 104 of type i, VNFs 102 of type k, must be at least aslarge as the required amount. The required amount may be represented bythe modularity constraint M(k, i), discussed above. This constraint maytake advantage of binary variable Y, as discussed above. Mathematically,this constraint may be represented as

${\sum\limits_{{lj} \in {LJ}}{\sum\limits_{v \in V}{X\left( {k,i,v,n,l,j} \right)}}} \geq {{Y\left( {k,n} \right)} \times {M\left( {k,i} \right)}}$

This constraint may be implemented as:

subject to ifSelectedAssigned{(k,i) in KI, n in N}:sum{(l, j) in LJ, v in V} X[k, i, v, n, l, j]>=Y[k, n]*M[k, i];

In addition to constraints, affinity and anti-affinity rules may also beconsisted in the integer programming problem. For example, an exemplaryanti-affinity rule may require that MCM VMs 104 a must be on a differentserver 112. That is, for each instance i of VNF 102 of type GW, at mostone MCM VM 104 a may be implemented on server 112 j. Mathematically,this may be represented by:

${\sum\limits_{n \in N}{\sum\limits_{v \in {VGW}}{X\left( {{GW},{MCM},v,n,l,j} \right)}}} \leq 1$

The above formula may be implemented as:

subject to MCMsOnDiffServers {(l, j) in LJ}:sum{n in N, v in VGW}X[GW, MCM, v, n, l, j]<=1;

Another anti-affinity rule may prevent assigning VNFs 102 except forgateway VNFs 102 a to server 112 on which ASM VM 104 b for anothergateway VNF 102 a is assigned. Additional variables or sets may be usedto represent or implement this rule. For example, variables ii may be amember of I, vv may be a member of V, and nn may be a member of N. Asanother example, a set IPCRF may include only those VMs 104 implementedfor PCRF VNFs 102 b, a set VPCRF may include only those VM 104 instancesthat are implemented for PCRF VNFs 102 b, and a set KNoGW may includeall VNF types k except for GW. (In our example, with K only includingtwo members: GW and PCRF, KNoGW would contain only PCRF).Mathematically, this may be represented by:

${\sum\limits_{k \in {KNoGW}}{\sum\limits_{{ii} \in {IPCRF}}{\sum\limits_{{vv} \in {VPCRF}}{\sum\limits_{{nn} \in N}{X\left( {k,{ii},{vv},{nn},l,j} \right)}}}}} \leq {1 - {X\left( {{GW},{ASM},v,n,l,j} \right)}}$

The above formula may be implemented as:

subject to ASMsonSameServerAndNoPCRFVMs {(l, j) in LJ, v in VGW, n inN}:sum{k in KNoGW, ii in IPCRF, vv in VPCRF, nn in N} X[k, ii, vv, nn, l,j]<=1−X [GW, ASM, v, n, l, j];

Another anti-affinity rule may prevent assigning any other VMs 104supporting any gateway VNFs 102 a (except for ASM VMs 104 b supportinggateway VNFs 102 a) from being assigned to the same server 112 as anyASM VMs 104 b instantiated for a gateway VNF 102 a. Additional variablesor sets may be used to represent or implement this rule. For example,INoASM may be a set of I that includes types of VMs 104 except for ASMVM 104 b. Mathematically, this may be represented by:

${\sum\limits_{{ii} \in {INoASM}}{\sum\limits_{{vv} \in {VGW}}{\sum\limits_{{nn} \in N}{X\left( {{GW},{ii},{vv},{nn},l,j} \right)}}}} \leq {1 - {X\left( {{GW},{ASM},v,n,l,j} \right)}}$

The above formula may be implemented as:

subject to ASMsOnSameServerAndNoGWVMs {(l, j) in LJ, v in VGW, n in N}:sum{ii in INoASM, vv in VGW, nn in N} X[GW, ii, vv, nn, l, j]<=1−X[GW,ASM, v, n, l, j];

Another anti-affinity rule may prevent assigning a VM 104 of type WSMfor a gateway VNF 102 a on the same server 112 as any VM 104 of type IOMfor a gateway VNF 102 a. Mathematically, this may be represented by:

X(GW,WSM,v,n,l,j)+X(GW,IOM,vv,nn,l,j)≤1

The above formula may be implemented as:

subject to WSMNotWithIOM{(l,j) in LJ, n in N, nn in N, v in VGW, vv inVVGW}:X[GW, WSM, v, n, l, j]+X[GW, IOM, vv, nn, l, j];where VVGW is a set identical to VGW.

Another anti-affinity rule may prevent assigning a VM 104 of type WSMfor a gateway VNF 102 a on the same server 112 as any ASM VM 104 b for agateway VNF 102 a. Mathematically, this may be represented by:

X(GW,WSM,v,n,l,j)+X(GW,ASM,vv,nn,l,j)≤1

The above formula may be implemented as:

subject to WSMNotWithASM{(l,j) in LJ, n in N, nn in N, v in VGW, vv inVVGW}:X[GW, WSM, v, n, l, j]+X[GW, ASM, vv, nn, l, j];

FIG. 2A illustrates a system 200 that may be used to configure network100, such as by inventorying and assigning resources 108 of hardwareplatform 106, to one or more VMs 104 or VNFs 102. System 200 mayconfigure network 100 using one or more steps of method 216 illustratedin the flowchart of FIG. 2B.

System 200 may be directly or indirectly communicatively connected tonetwork 100. At step 218, system 200 may receive a network profile 202from network 100. Network profile 202 may include data indicative of oneor more sets or members of sets of data pertaining to the elements ofnetwork 100. For example, network profile 202 may indicate the inventoryof hardware platform 106, including the number, type, and capacity ofchasses 110. For example, network profile 202 may identify the numberand type of servers 112 in each chassis 110. Additionally oralternatively, network profile 202 may identify the number and type ofresources 108 in each server 112. Network profile 202 may indicate whichresources 108, servers 112, or chasses 110 are available, operatingproperly, assigned to one or more VM 104 or VNF 102, malfunctioning,offline, or the like. Network profile 202 may include (data that may beused to at least partially build) one or more sets (e.g., sets L, J, LJ,I, IPRF, INoASM, K, KNoGW, KNoPCRF, KI, N, V, VGW, VPCRF, VV, VVGW, orthe like). Network profile 202 may include (data that may be used to atleast partially define) certain parameters that may indicate thecapacity or requirements of certain network elements—including virtualcomponents, like VNFs 102 or VMs 104, and hardware platform 106components, like resources 108, chassis 110, or servers 112. Theseparameters may include, for example, the capacity for VNF 102 cluster,such as in sessions (e.g., Ck), the vCPU 108 a requirement for VM 104(e.g., Cki) memory 108 b requirement for VM 104 (e.g., Rki), NIC 108 arequirement for a VM 104 (e.g., Nki), the capacity of vCPUs 108 a inserver 112 (e.g., Clj), the capacity of memory 108 b in server 112(e.g., Rlj), the capacity of NICs 108 c in server 112 (e.g., Nlj) thetotal vCPUs 108 a allocated for gateway VNFs 102 a (e.g., virtualCPUgw),the total vCPUs 108 a allocated for PCRF VNFs 102 b (e.g.,virtualCPUpcrf), the total memory 108 b allocated for gateway VNFs 102 a(e.g., virtualMemoryGW), the total memory 108 b allocated for PCRF VNFs102 b (e.g., virtualMemoryPCRF), the total NICs 108 c allocated forgateway VNFs 102 a (e.g., virtualNICgw), the total NICs 108 c allocatedfor PCRF VNFs 102 b (e.g., virtualNICpcrf), or the like.

System 200 may include a configuration engine 204 into which networkprofile 202 (or at least a portion of data of network profile 202) maybe input. Network profile 202 information may be processed by aconfiguration engine 204 to determine how to configure network 100 thatprovides a greater number of sessions while still complying withapplicable constraints and rules. Configuration engine 204 may includean objective function 206. For example, the objective function may bedesigned to maximize or increase the total capacity of network 100.

Configuration engine 204 may include one or more constraints 208. Theconstraints, as discussed above, may restrict or define the totalcapacity of network 100. For example, constraints 208 may includelimitations that the total capacity of network 100 is less than or equalto any of the total capacity of a given type k of VNFs 102. As anotherexample, the total allocated resources 108 of a given type (e.g., vCPUs108 a) cannot be greater than the maximum number of such resources inthat server 112 (e.g., virtualCPU). Another constraint may be that inorder to assign an instance of type k of VNF 102 to a chassis 110 andserver 112, network 100 needs to be using that instance of type k of VNF102. Another constraint may be that for a given server 112 and chassis110, the sum of the number of VMs 104 of type i, VNF 102 type k, must beat least as large as the required amount (which may be determined byM(k, i)).

At step 220, system 200 may determine one or more configurations ofnetwork 100 based on the constraints and network profile 202. Forexample, this may include identifying configurations of network 100 thatsatisfy one or more of the constraints. This network.

Configuration engine 205 may include one or more affinity rules 210 oranti-affinity rules 212 that may also restrict configuration of network100. For example, as discussed above, affinity rules may require thatcertain elements be assigned to the same server 112 or chassis 110,while anti-affinity rules may require that certain other elements beassigned to separate servers 112 or chasses 110.

At step 222, system 200 may identify configurations that satisfy one ormore affinity rules or anti-affinity rules. In an aspect, theconfigurations identified at step 222 may comprise a subset of theconfigurations identified at step 220. Additionally or alternatively,step 220 and step 222 may be performed simultaneously, so a set ofconfigurations that satisfy both the constraints and the one or moreaffinity or anti-affinity rules are identified.

At step 224, system 200 may use objective function 206 to identify oneor more of the configurations that supports a greater number ofsessions. For example, the objective function 206 may select networkconfiguration 214, which satisfies constraints 208, affinity rules 210,and anti-affinity rules 212 and that, within those bounds, provides agreater number of sessions (e.g., maximizing the capacity) set forth inobjective function 206.

In an aspect, one or more of steps 220 through 224 may be performed byconsidering one or more of the formulas disclosed above, or by executingone or more implementations of the integer programming problem disclosedabove.

At step 226, network 100 may be configured according to networkconfiguration 214. This may include, for example, assigning one or moreVMs 104 or VNFs 102 to one or more servers 112.

FIG. 3 is a block diagram of network device 300 that may be connected toor comprise a component of network 100 or system 200. Network device 300may comprise hardware or a combination of hardware and software. Thefunctionality to facilitate telecommunications via a telecommunicationsnetwork may reside in one or combination of network devices 300. Networkdevice 300 depicted in FIG. 3 may represent or perform functionality ofan appropriate network device 300, or combination of network devices300, such as, for example, a component or various components of acellular broadcast system wireless network, a processor, a server, agateway, a node, a mobile switching center (MSC), a short messageservice center (SMSC), an ALFS, a gateway mobile location center (GMLC),a radio access network (RAN), a serving mobile location center (SMLC),or the like, or any appropriate combination thereof. It is emphasizedthat the block diagram depicted in FIG. 3 is exemplary and not intendedto imply a limitation to a specific implementation or configuration.Thus, network device 300 may be implemented in a single device ormultiple devices (e.g., single server or multiple servers, singlegateway or multiple gateways, single controller or multiplecontrollers). Multiple network entities may be distributed or centrallylocated. Multiple network entities may communicate wirelessly, via hardwire, or any appropriate combination thereof.

Network device 300 may comprise a processor 302 and a memory 304 coupledto processor 302. Memory 304 may contain executable instructions that,when executed by processor 302, cause processor 302 to effectuateoperations associated with mapping wireless signal strength. As evidentfrom the description herein, network device 300 is not to be construedas software per se.

In addition to processor 302 and memory 304, network device 300 mayinclude an input/output system 306. Processor 302, memory 304, andinput/output system 306 may be coupled together (coupling not shown inFIG. 3) to allow communications therebetween. Each portion of networkdevice 300 may comprise circuitry for performing functions associatedwith each respective portion. Thus, each portion may comprise hardware,or a combination of hardware and software. Accordingly, each portion ofnetwork device 300 is not to be construed as software per se.Input/output system 306 may be capable of receiving or providinginformation from or to a communications device or other network entitiesconfigured for telecommunications. For example input/output system 306may include a wireless communications (e.g., 3G/4G/GPS) card.Input/output system 306 may be capable of receiving or sending videoinformation, audio information, control information, image information,data, or any combination thereof. Input/output system 306 may be capableof transferring information with network device 300. In variousconfigurations, input/output system 306 may receive or provideinformation via any appropriate means, such as, for example, opticalmeans (e.g., infrared), electromagnetic means (e.g., RF, Wi-Fi,Bluetooth®, ZigBee®), acoustic means (e.g., speaker, microphone,ultrasonic receiver, ultrasonic transmitter), or a combination thereof.In an example configuration, input/output system 306 may comprise aWi-Fi finder, a two-way GPS chipset or equivalent, or the like, or acombination thereof.

Input/output system 306 of network device 300 also may contain acommunication connection 308 that allows network device 300 tocommunicate with other devices, network entities, or the like.Communication connection 308 may comprise communication media.Communication media typically embody computer-readable instructions,data structures, program modules or other data in a modulated datasignal such as a carrier wave or other transport mechanism and includesany information delivery media. By way of example, and not limitation,communication media may include wired media such as a wired network ordirect-wired connection, or wireless media such as acoustic, RF,infrared, or other wireless media. The term computer-readable media asused herein includes both storage media and communication media.Input/output system 306 also may include an input device 310 such askeyboard, mouse, pen, voice input device, or touch input device.Input/output system 306 may also include an output device 312, such as adisplay, speakers, or a printer.

Processor 302 may be capable of performing functions associated withtelecommunications, such as functions for processing broadcast messages,as described herein. For example, processor 302 may be capable of, inconjunction with any other portion of network device 300, determining atype of broadcast message and acting according to the broadcast messagetype or content, as described herein.

Memory 304 of network device 300 may comprise a storage medium having aconcrete, tangible, physical structure. As is known, a signal does nothave a concrete, tangible, physical structure. Memory 304, as well asany computer-readable storage medium described herein, is not to beconstrued as a signal. Memory 304, as well as any computer-readablestorage medium described herein, is not to be construed as a transientsignal. Memory 304, as well as any computer-readable storage mediumdescribed herein, is not to be construed as a propagating signal. Memory304, as well as any computer-readable storage medium described herein,is to be construed as an article of manufacture.

Memory 304 may store any information utilized in conjunction withtelecommunications. Depending upon the exact configuration or type ofprocessor, memory 304 may include a volatile storage 314 (such as sometypes of RAM), a nonvolatile storage 316 (such as ROM, flash memory), ora combination thereof. Memory 304 may include additional storage (e.g.,a removable storage 318 or a nonremovable storage 320) including, forexample, tape, flash memory, smart cards, CD-ROM, DVD, or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, USB-compatible memory, or any othermedium that can be used to store information and that can be accessed bynetwork device 300. Memory 304 may comprise executable instructionsthat, when executed by processor 302, cause processor 302 to effectuateoperations to map signal strengths in an area of interest.

FIG. 4 illustrates a functional block diagram depicting one example ofan LTE-EPS network architecture 400 that may be at least partiallyimplemented as using virtualized functions. Network architecture 400disclosed herein is referred to as a modified LTE-EPS architecture 400to distinguish it from a traditional LTE-EPS architecture.

An example modified LTE-EPS architecture 400 is based at least in parton standards developed by the 3rd Generation Partnership Project (3GPP),with information available at www.3gpp.org. LTE-EPS network architecture400 may include an access network 402, a core network 404, e.g., an EPCor Common BackBone (CBB) and one or more external networks 406,sometimes referred to as PDN or peer entities. Different externalnetworks 406 can be distinguished from each other by a respectivenetwork identifier, e.g., a label according to DNS naming conventionsdescribing an access point to the PDN. Such labels can be referred to asAccess Point Names (APN). External networks 406 can include one or moretrusted and non-trusted external networks such as an internet protocol(IP) network 408, an IP multimedia subsystem (IMS) network 410, andother networks 412, such as a service network, a corporate network, orthe like. In an aspect, access network 402, core network 404, orexternal network 405 may include or communicate with network 100.

Access network 402 can include an LTE network architecture sometimesreferred to as Evolved Universal mobile Telecommunication systemTerrestrial Radio Access (E UTRA) and evolved UMTS Terrestrial RadioAccess Network (E-UTRAN). Broadly, access network 402 can include one ormore communication devices, commonly referred to as UE 414, and one ormore wireless access nodes, or base stations 416 a, 416 b. Duringnetwork operations, at least one base station 416 communicates directlywith UE 414. Base station 416 can be an evolved Node B (e-NodeB), withwhich UE 414 communicates over the air and wirelessly. UEs 414 caninclude, without limitation, wireless devices, e.g., satellitecommunication systems, portable digital assistants (PDAs), laptopcomputers, tablet devices and other mobile devices (e.g., cellulartelephones, smart appliances, and so on). UEs 414 can connect to eNBs416 when UE 414 is within range according to a corresponding wirelesscommunication technology.

UE 414 generally runs one or more applications that engage in a transferof packets between UE 414 and one or more external networks 406. Suchpacket transfers can include one of downlink packet transfers fromexternal network 406 to UE 414, uplink packet transfers from UE 414 toexternal network 406 or combinations of uplink and downlink packettransfers. Applications can include, without limitation, web browsing,VoIP, streaming media and the like. Each application can pose differentQuality of Service (QoS) requirements on a respective packet transfer.Different packet transfers can be served by different bearers withincore network 404, e.g., according to parameters, such as the QoS.

Core network 404 uses a concept of bearers, e.g., EPS bearers, to routepackets, e.g., IP traffic, between a particular gateway in core network404 and UE 414. A bearer refers generally to an IP packet flow with adefined QoS between the particular gateway and UE 414. Access network402, e.g., E UTRAN, and core network 404 together set up and releasebearers as required by the various applications. Bearers can beclassified in at least two different categories: (i) minimum guaranteedbit rate bearers, e.g., for applications, such as VoIP; and (ii)non-guaranteed bit rate bearers that do not require guarantee bit rate,e.g., for applications, such as web browsing.

In one embodiment, the core network 404 includes various networkentities, such as MME 418, SGW 420, Home Subscriber Server (HSS) 422,Policy and Charging Rules Function (PCRF) 424 and PGW 426. In oneembodiment, MME 418 comprises a control node performing a controlsignaling between various equipment and devices in access network 402and core network 404. The protocols running between UE 414 and corenetwork 404 are generally known as Non-Access Stratum (NAS) protocols.

For illustration purposes only, the terms MME 418, SGW 420, HSS 422 andPGW 426, and so on, can be server devices, but may be referred to in thesubject disclosure without the word “server.” It is also understood thatany form of such servers can operate in a device, system, component, orother form of centralized or distributed hardware and software. It isfurther noted that these terms and other terms such as bearer pathsand/or interfaces are terms that can include features, methodologies,and/or fields that may be described in whole or in part by standardsbodies such as the 3GPP. It is further noted that some or allembodiments of the subject disclosure may in whole or in part modify,supplement, or otherwise supersede final or proposed standards publishedand promulgated by 3GPP.

According to traditional implementations of LTE-EPS architectures, SGW420 routes and forwards all user data packets. SGW 420 also acts as amobility anchor for user plane operation during handovers between basestations, e.g., during a handover from first eNB 416 a to second eNB 416b as may be the result of UE 414 moving from one area of coverage, e.g.,cell, to another. SGW 420 can also terminate a downlink data path, e.g.,from external network 406 to UE 414 in an idle state, and trigger apaging operation when downlink data arrives for UE 414. SGW 420 can alsobe configured to manage and store a context for UE 414, e.g., includingone or more of parameters of the IP bearer service and network internalrouting information. In addition, SGW 420 can perform administrativefunctions, e.g., in a visited network, such as collecting informationfor charging (e.g., the volume of data sent to or received from theuser), and/or replicate user traffic, e.g., to support a lawfulinterception. SGW 420 also serves as the mobility anchor forinterworking with other 3GPP technologies such as universal mobiletelecommunication system (UMTS).

At any given time, UE 414 is generally in one of three different states:detached, idle, or active. The detached state is typically a transitorystate in which UE 414 is powered on but is engaged in a process ofsearching and registering with network 402. In the active state, UE 414is registered with access network 402 and has established a wirelessconnection, e.g., radio resource control (RRC) connection, with eNB 416.Whether UE 414 is in an active state can depend on the state of a packetdata session, and whether there is an active packet data session. In theidle state, UE 414 is generally in a power conservation state in whichUE 414 typically does not communicate packets. When UE 414 is idle, SGW420 can terminate a downlink data path, e.g., from one peer entity, andtriggers paging of UE 414 when data arrives for UE 414. If UE 414responds to the page, SGW 420 can forward the IP packet to eNB 416 a.

HSS 422 can manage subscription-related information for a user of UE414. For example, tHSS 422 can store information such as authorizationof the user, security requirements for the user, quality of service(QoS) requirements for the user, etc. HSS 422 can also hold informationabout external networks 406 to which the user can connect, e.g., in theform of an APN of external networks 406. For example, MME 418 cancommunicate with HSS 422 to determine if UE 414 is authorized toestablish a call, e.g., a voice over IP (VoIP) call before the call isestablished.

PCRF 424 can perform QoS management functions and policy control. PCRF424 is responsible for policy control decision-making, as well as forcontrolling the flow-based charging functionalities in a policy controlenforcement function (PCEF), which resides in PGW 426. PCRF 424 providesthe QoS authorization, e.g., QoS class identifier and bit rates thatdecide how a certain data flow will be treated in the PCEF and ensuresthat this is in accordance with the user's subscription profile.

PGW 426 can provide connectivity between the UE 414 and one or more ofthe external networks 406. In illustrative network architecture 400, PGW426 can be responsible for IP address allocation for UE 414, as well asone or more of QoS enforcement and flow-based charging, e.g., accordingto rules from the PCRF 424. PGW 426 is also typically responsible forfiltering downlink user IP packets into the different QoS-based bearers.In at least some embodiments, such filtering can be performed based ontraffic flow templates. PGW 426 can also perform QoS enforcement, e.g.,for guaranteed bit rate bearers. PGW 426 also serves as a mobilityanchor for interworking with non-3GPP technologies such as CDMA2000.

Within access network 402 and core network 404 there may be variousbearer paths/interfaces, e.g., represented by solid lines 428 and 430.Some of the bearer paths can be referred to by a specific label. Forexample, solid line 428 can be considered an S1-U bearer and solid line432 can be considered an S5/S8 bearer according to LTE-EPS architecturestandards. Without limitation, reference to various interfaces, such asS1, X2, S5, S8, S11 refer to EPS interfaces. In some instances, suchinterface designations are combined with a suffix, e.g., a “U” or a “C”to signify whether the interface relates to a “User plane” or a “Controlplane.” In addition, the core network 404 can include various signalingbearer paths/interfaces, e.g., control plane paths/interfacesrepresented by dashed lines 430, 434, 436, and 438. Some of thesignaling bearer paths may be referred to by a specific label. Forexample, dashed line 430 can be considered as an Sl-MME signalingbearer, dashed line 434 can be considered as an S11 signaling bearer anddashed line 436 can be considered as an S6a signaling bearer, e.g.,according to LTE-EPS architecture standards. The above bearer paths andsignaling bearer paths are only illustrated as examples and it should benoted that additional bearer paths and signaling bearer paths may existthat are not illustrated.

Also shown is a novel user plane path/interface, referred to as theS1-U+ interface 466. In the illustrative example, the S1-U+ user planeinterface extends between the eNB 416 a and PGW 426. Notably, S1-U+path/interface does not include SGW 420, a node that is otherwiseinstrumental in configuring and/or managing packet forwarding betweeneNB 416 a and one or more external networks 406 by way of PGW 426. Asdisclosed herein, the S1-U+ path/interface facilitates autonomouslearning of peer transport layer addresses by one or more of the networknodes to facilitate a self-configuring of the packet forwarding path. Inparticular, such self-configuring can be accomplished during handoversin most scenarios so as to reduce any extra signaling load on the S/PGWs420, 426 due to excessive handover events.

In some embodiments, PGW 426 is coupled to storage device 440, shown inphantom. Storage device 440 can be integral to one of the network nodes,such as PGW 426, for example, in the form of internal memory and/or diskdrive. It is understood that storage device 440 can include registerssuitable for storing address values. Alternatively or in addition,storage device 440 can be separate from PGW 426, for example, as anexternal hard drive, a flash drive, and/or network storage.

Storage device 440 selectively stores one or more values relevant to theforwarding of packet data. For example, storage device 440 can storeidentities and/or addresses of network entities, such as any of networknodes 418, 420, 422, 424, and 426, eNBs 416 and/or UE 414. In theillustrative example, storage device 440 includes a first storagelocation 442 and a second storage location 444. First storage location442 can be dedicated to storing a Currently Used Downlink address value442. Likewise, second storage location 444 can be dedicated to storing aDefault Downlink Forwarding address value 444. PGW 426 can read and/orwrite values into either of storage locations 442, 444, for example,managing Currently Used Downlink Forwarding address value 442 andDefault Downlink Forwarding address value 444 as disclosed herein.

In some embodiments, the Default Downlink Forwarding address for eachEPS bearer is the SGW S5-U address for each EPS Bearer. The CurrentlyUsed Downlink Forwarding address” for each EPS bearer in PGW 426 can beset every time when PGW 426 receives an uplink packet, e.g., a GTP-Uuplink packet, with a new source address for a corresponding EPS bearer.When UE 414 is in an idle state, the “Current Used Downlink Forwardingaddress” field for each EPS bearer of UE 414 can be set to a “null” orother suitable value.

In some embodiments, the Default Downlink Forwarding address is onlyupdated when PGW 426 receives a new SGW S5-U address in a predeterminedmessage or messages. For example, the Default Downlink Forwardingaddress is only updated when PGW 426 receives one of a Create SessionRequest, Modify Bearer Request and Create Bearer Response messages fromSGW 420.

As values 442, 444 can be maintained and otherwise manipulated on a perbearer basis, it is understood that the storage locations can take theform of tables, spreadsheets, lists, and/or other data structuresgenerally well understood and suitable for maintaining and/or otherwisemanipulate forwarding addresses on a per bearer basis.

It should be noted that access network 402 and core network 404 areillustrated in a simplified block diagram in FIG. 4. In other words,either or both of access network 402 and the core network 404 caninclude additional network elements that are not shown, such as variousrouters, switches and controllers. In addition, although FIG. 4illustrates only a single one of each of the various network elements,it should be noted that access network 402 and core network 404 caninclude any number of the various network elements. For example, corenetwork 404 can include a pool (i.e., more than one) of MMEs 418, SGWs420 or PGWs 426.

In the illustrative example, data traversing a network path between UE414, eNB 416 a, SGW 420, PGW 426 and external network 406 may beconsidered to constitute data transferred according to an end-to-end IPservice. However, for the present disclosure, to properly performestablishment management in LTE-EPS network architecture 400, the corenetwork, data bearer portion of the end-to-end IP service is analyzed.

An establishment may be defined herein as a connection set up requestbetween any two elements within LTE-EPS network architecture 400. Theconnection set up request may be for user data or for signaling. Afailed establishment may be defined as a connection set up request thatwas unsuccessful. A successful establishment may be defined as aconnection set up request that was successful.

In one embodiment, a data bearer portion comprises a first portion(e.g., a data radio bearer 446) between UE 414 and eNB 416 a, a secondportion (e.g., an S1 data bearer 428) between eNB 416 a and SGW 420, anda third portion (e.g., an S5/S8 bearer 432) between SGW 420 and PGW 426.Various signaling bearer portions are also illustrated in FIG. 4. Forexample, a first signaling portion (e.g., a signaling radio bearer 448)between UE 414 and eNB 416 a, and a second signaling portion (e.g., S1signaling bearer 430) between eNB 416 a and MME 418.

In at least some embodiments, the data bearer can include tunneling,e.g., IP tunneling, by which data packets can be forwarded in anencapsulated manner, between tunnel endpoints. Tunnels, or tunnelconnections can be identified in one or more nodes of network 100, e.g.,by one or more of tunnel endpoint identifiers, an IP address and a userdatagram protocol port number. Within a particular tunnel connection,payloads, e.g., packet data, which may or may not include protocolrelated information, are forwarded between tunnel endpoints.

An example of first tunnel solution 450 includes a first tunnel 452 abetween two tunnel endpoints 454 a and 456 a, and a second tunnel 452 bbetween two tunnel endpoints 454 b and 456 b. In the illustrativeexample, first tunnel 452 a is established between eNB 416 a and SGW420. Accordingly, first tunnel 452 a includes a first tunnel endpoint454 a corresponding to an S1-U address of eNB 416 a (referred to hereinas the eNB S1-U address), and second tunnel endpoint 456 a correspondingto an S1-U address of SGW 420 (referred to herein as the SGW S1-Uaddress). Likewise, second tunnel 452 b includes first tunnel endpoint454 b corresponding to an S5-U address of SGW 420 (referred to herein asthe SGW S5-U address), and second tunnel endpoint 456 b corresponding toan S5-U address of PGW 426 (referred to herein as the PGW S5-U address).

In at least some embodiments, first tunnel solution 450 is referred toas a two tunnel solution, e.g., according to the GPRS Tunneling ProtocolUser Plane (GTPv1-U based), as described in 3GPP specification TS29.281, incorporated herein in its entirety. It is understood that oneor more tunnels are permitted between each set of tunnel end points. Forexample, each subscriber can have one or more tunnels, e.g., one foreach PDP context that they have active, as well as possibly havingseparate tunnels for specific connections with different quality ofservice requirements, and so on.

An example of second tunnel solution 458 includes a single or directtunnel 460 between tunnel endpoints 462 and 464. In the illustrativeexample, direct tunnel 460 is established between eNB 416 a and PGW 426,without subjecting packet transfers to processing related to SGW 420.Accordingly, direct tunnel 460 includes first tunnel endpoint 462corresponding to the eNB S1-U address, and second tunnel endpoint 464corresponding to the PGW S5-U address. Packet data received at eitherend can be encapsulated into a payload and directed to the correspondingaddress of the other end of the tunnel. Such direct tunneling avoidsprocessing, e.g., by SGW 420 that would otherwise relay packets betweenthe same two endpoints, e.g., according to a protocol, such as the GTP-Uprotocol.

In some scenarios, direct tunneling solution 458 can forward user planedata packets between eNB 416 a and PGW 426, by way of SGW 420. That is,SGW 420 can serve a relay function, by relaying packets between twotunnel endpoints 416 a, 426. In other scenarios, direct tunnelingsolution 458 can forward user data packets between eNB 416 a and PGW426, by way of the S1 U+ interface, thereby bypassing SGW 420.

Generally, UE 414 can have one or more bearers at any one time. Thenumber and types of bearers can depend on applications, defaultrequirements, and so on. It is understood that the techniques disclosedherein, including the configuration, management and use of varioustunnel solutions 450, 458, can be applied to the bearers on anindividual bases. That is, if user data packets of one bearer, say abearer associated with a VoIP service of UE 414, then the forwarding ofall packets of that bearer are handled in a similar manner. Continuingwith this example, the same UE 414 can have another bearer associatedwith it through the same eNB 416 a. This other bearer, for example, canbe associated with a relatively low rate data session forwarding userdata packets through core network 404 simultaneously with the firstbearer. Likewise, the user data packets of the other bearer are alsohandled in a similar manner, without necessarily following a forwardingpath or solution of the first bearer. Thus, one of the bearers may beforwarded through direct tunnel 458; whereas, another one of the bearersmay be forwarded through a two-tunnel solution 450.

FIG. 5 depicts an exemplary diagrammatic representation of a machine inthe form of a computer system 500 within which a set of instructions,when executed, may cause the machine to perform any one or more of themethods described above. One or more instances of the machine canoperate, for example, as processor 302, UE 414, eNB 416, MME 418, SGW420, HSS 422, PCRF 424, PGW 426 and other devices of FIGS. 1, 2, and 4.In some embodiments, the machine may be connected (e.g., using a network502) to other machines. In a networked deployment, the machine mayoperate in the capacity of a server or a client user machine in aserver-client user network environment, or as a peer machine in apeer-to-peer (or distributed) network environment.

The machine may comprise a server computer, a client user computer, apersonal computer (PC), a tablet, a smart phone, a laptop computer, adesktop computer, a control system, a network router, switch or bridge,or any machine capable of executing a set of instructions (sequential orotherwise) that specify actions to be taken by that machine. It will beunderstood that a communication device of the subject disclosureincludes broadly any electronic device that provides voice, video ordata communication. Further, while a single machine is illustrated, theterm “machine” shall also be taken to include any collection of machinesthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methods discussed herein.

Computer system 500 may include a processor (or controller) 504 (e.g., acentral processing unit (CPU)), a graphics processing unit (GPU, orboth), a main memory 506 and a static memory 508, which communicate witheach other via a bus 510. The computer system 500 may further include adisplay unit 512 (e.g., a liquid crystal display (LCD), a flat panel, ora solid state display). Computer system 500 may include an input device514 (e.g., a keyboard), a cursor control device 516 (e.g., a mouse), adisk drive unit 518, a signal generation device 520 (e.g., a speaker orremote control) and a network interface device 522. In distributedenvironments, the embodiments described in the subject disclosure can beadapted to utilize multiple display units 512 controlled by two or morecomputer systems 500. In this configuration, presentations described bythe subject disclosure may in part be shown in a first of display units512, while the remaining portion is presented in a second of displayunits 512.

The disk drive unit 518 may include a tangible computer-readable storagemedium 524 on which is stored one or more sets of instructions (e.g.,software 526) embodying any one or more of the methods or functionsdescribed herein, including those methods illustrated above.Instructions 526 may also reside, completely or at least partially,within main memory 506, static memory 508, or within processor 504during execution thereof by the computer system 500. Main memory 506 andprocessor 504 also may constitute tangible computer-readable storagemedia.

As shown in FIG. 6, telecommunication system 600 may include wirelesstransmit/receive units (WTRUs) 602, a RAN 604, a core network 606, apublic switched telephone network (PSTN) 608, the Internet 610, or othernetworks 612, though it will be appreciated that the disclosed examplescontemplate any number of WTRUs, base stations, networks, or networkelements. Each WTRU 602 may be any type of device configured to operateor communicate in a wireless environment. For example, a WTRU maycomprise a mobile device, network device 300, or the like, or anycombination thereof. By way of example, WTRUs 602 may be configured totransmit or receive wireless signals and may include a UE, a mobilestation, a mobile device, a fixed or mobile subscriber unit, a pager, acellular telephone, a PDA, a smartphone, a laptop, a netbook, a personalcomputer, a wireless sensor, consumer electronics, or the like. WTRUs602 may be configured to transmit or receive wireless signals over anair interface 614.

Telecommunication system 600 may also include one or more base stations616. Each of base stations 616 may be any type of device configured towirelessly interface with at least one of the WTRUs 602 to facilitateaccess to one or more communication networks, such as core network 606,PTSN 608, Internet 610, or other networks 612. By way of example, basestations 616 may be a base transceiver station (BTS), a Node-B, an eNodeB, a Home Node B, a Home eNode B, a site controller, an access point(AP), a wireless router, or the like. While base stations 616 are eachdepicted as a single element, it will be appreciated that base stations616 may include any number of interconnected base stations or networkelements.

RAN 604 may include one or more base stations 616, along with othernetwork elements (not shown), such as a base station controller (BSC), aradio network controller (RNC), or relay nodes. One or more basestations 616 may be configured to transmit or receive wireless signalswithin a particular geographic region, which may be referred to as acell (not shown). The cell may further be divided into cell sectors. Forexample, the cell associated with base station 616 may be divided intothree sectors such that base station 616 may include three transceivers:one for each sector of the cell. In another example, base station 616may employ multiple-input multiple-output (MIMO) technology and,therefore, may utilize multiple transceivers for each sector of thecell.

Base stations 616 may communicate with one or more of WTRUs 602 over airinterface 614, which may be any suitable wireless communication link(e.g., RF, microwave, infrared (IR), ultraviolet (UV), or visiblelight). Air interface 614 may be established using any suitable radioaccess technology (RAT).

More specifically, as noted above, telecommunication system 600 may be amultiple access system and may employ one or more channel accessschemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, or the like. Forexample, base station 616 in RAN 604 and WTRUs 602 connected to RAN 604may implement a radio technology such as Universal MobileTelecommunications System (UMTS) Terrestrial Radio Access (UTRA) thatmay establish air interface 614 using wideband CDMA (WCDMA). WCDMA mayinclude communication protocols, such as High-Speed Packet Access (HSPA)or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink PacketAccess (HSDPA) or High-Speed Uplink Packet Access (HSUPA).

As another example base station 616 and WTRUs 602 that are connected toRAN 604 may implement a radio technology such as Evolved UMTSTerrestrial Radio Access (E-UTRA), which may establish air interface 614using LTE or LTE-Advanced (LTE-A).

Optionally base station 616 and WTRUs 602 connected to RAN 604 mayimplement radio technologies such as IEEE 602.16 (i.e., WorldwideInteroperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1×,CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95(IS-95), Interim Standard 856 (IS-856), GSM, Enhanced Data rates for GSMEvolution (EDGE), GSM EDGE (GERAN), or the like.

Base station 616 may be a wireless router, Home Node B, Home eNode B, oraccess point, for example, and may utilize any suitable RAT forfacilitating wireless connectivity in a localized area, such as a placeof business, a home, a vehicle, a campus, or the like. For example, basestation 616 and associated WTRUs 602 may implement a radio technologysuch as IEEE 602.11 to establish a wireless local area network (WLAN).As another example, base station 616 and associated WTRUs 602 mayimplement a radio technology such as IEEE 602.15 to establish a wirelesspersonal area network (WPAN). In yet another example, base station 616and associated WTRUs 602 may utilize a cellular-based RAT (e.g., WCDMA,CDMA2000, GSM, LTE, LTE-A, etc.) to establish a picocell or femtocell.As shown in FIG. 6, base station 616 may have a direct connection toInternet 610. Thus, base station 616 may not be required to accessInternet 610 via core network 606.

RAN 604 may be in communication with core network 606, which may be anytype of network configured to provide voice, data, applications, and/orvoice over internet protocol (VoIP) services to one or more WTRUs 602.For example, core network 606 may provide call control, billingservices, mobile location-based services, pre-paid calling, Internetconnectivity, video distribution or high-level security functions, suchas user authentication. Although not shown in FIG. 6, it will beappreciated that RAN 604 or core network 606 may be in direct orindirect communication with other RANs that employ the same RAT as RAN604 or a different RAT. For example, in addition to being connected toRAN 604, which may be utilizing an E-UTRA radio technology, core network606 may also be in communication with another RAN (not shown) employinga GSM radio technology.

Core network 606 may also serve as a gateway for WTRUs 602 to accessPSTN 608, Internet 610, or other networks 612. PSTN 608 may includecircuit-switched telephone networks that provide plain old telephoneservice (POTS). For LTE core networks, core network 606 may use IMS core614 to provide access to PSTN 608. Internet 610 may include a globalsystem of interconnected computer networks or devices that use commoncommunication protocols, such as the transmission control protocol(TCP), user datagram protocol (UDP), or IP in the TCP/IP internetprotocol suite. Other networks 612 may include wired or wirelesscommunications networks owned or operated by other service providers.For example, other networks 612 may include another core networkconnected to one or more RANs, which may employ the same RAT as RAN 604or a different RAT.

Some or all WTRUs 602 in telecommunication system 600 may includemulti-mode capabilities. That is, WTRUs 602 may include multipletransceivers for communicating with different wireless networks overdifferent wireless links. For example, one or more WTRUs 602 may beconfigured to communicate with base station 616, which may employ acellular-based radio technology, and with base station 616, which mayemploy an IEEE 802 radio technology.

FIG. 7 is an example system 700 including RAN 604 and core network 606.As noted above, RAN 604 may employ an E-UTRA radio technology tocommunicate with WTRUs 602 over air interface 614. RAN 604 may also bein communication with core network 606.

RAN 604 may include any number of eNode-Bs 702 while remainingconsistent with the disclosed technology. One or more eNode-Bs 702 mayinclude one or more transceivers for communicating with the WTRUs 602over air interface 614. Optionally, eNode-Bs 702 may implement MIMOtechnology. Thus, one of eNode-Bs 702, for example, may use multipleantennas to transmit wireless signals to, or receive wireless signalsfrom, one of WTRUs 602.

Each of eNode-Bs 702 may be associated with a particular cell (notshown) and may be configured to handle radio resource managementdecisions, handover decisions, scheduling of users in the uplink ordownlink, or the like. As shown in FIG. 7 eNode-Bs 702 may communicatewith one another over an X2 interface.

Core network 606 shown in FIG. 7 may include a mobility managementgateway or entity (MME) 704, a serving gateway 706, or a packet datanetwork (PDN) gateway 708. While each of the foregoing elements aredepicted as part of core network 606, it will be appreciated that anyone of these elements may be owned or operated by an entity other thanthe core network operator.

MME 704 may be connected to each of eNode-Bs 702 in RAN 604 via an S1interface and may serve as a control node. For example, MME 704 may beresponsible for authenticating users of WTRUs 602, bearer activation ordeactivation, selecting a particular serving gateway during an initialattach of WTRUs 602, or the like. MME 704 may also provide a controlplane function for switching between RAN 604 and other RANs (not shown)that employ other radio technologies, such as GSM or WCDMA.

Serving gateway 706 may be connected to each of eNode-Bs 702 in RAN 604via the S1 interface. Serving gateway 706 may generally route or forwarduser data packets to or from the WTRUs 602. Serving gateway 706 may alsoperform other functions, such as anchoring user planes duringinter-eNode B handovers, triggering paging when downlink data isavailable for WTRUs 602, managing or storing contexts of WTRUs 602, orthe like.

Serving gateway 706 may also be connected to PDN gateway 708, which mayprovide WTRUs 602 with access to packet-switched networks, such asInternet 610, to facilitate communications between WTRUs 602 andIP-enabled devices.

Core network 606 may facilitate communications with other networks. Forexample, core network 606 may provide WTRUs 602 with access tocircuit-switched networks, such as PSTN 608, such as through IMS core614, to facilitate communications between WTRUs 602 and traditionalland-line communications devices. In addition, core network 606 mayprovide the WTRUs 602 with access to other networks 612, which mayinclude other wired or wireless networks that are owned or operated byother service providers.

1. A method comprising: receiving profile information for a network;determining a network configuration based on at least an anti-affinityrule and a constraint associated with at least one of a network sessionor a hardware capacity of a hardware platform of the network and anumber of sessions to be supported by the network configured based onthe network configuration; and configuring the network based on thenetwork configuration, wherein the network configuration assigns atleast one instantiation of a virtual machine (VM) of a first VM type forat least one instantiation of a virtual network function (VNF) of afirst VNF type to at least one server of the hardware platform.
 2. Themethod of claim 1, wherein determining the network configurationcomprises: identifying a plurality of configurations that satisfy theconstraint; and selecting the network configuration from the pluralityof configurations based on the network configuration supporting a highernumber of sessions compared to others of the plurality ofconfigurations.
 3. The method of claim 1, wherein determining thenetwork configuration is further based on an affinity rule.
 4. Themethod of claim 1, wherein determining the network configuration isfurther based on a second anti-affinity rule.
 5. The method of claim 1,wherein the network profile is indicative of an inventory of thenetwork.
 6. The method of claim 1, wherein the network configurationassigns a second VM to a second server of the hardware platform.
 7. Themethod of claim 6, wherein the second VM is used to at least partiallyimplement the VNF.
 8. A method comprising: identifying a plurality ofconfigurations of a network that satisfies an anti-affinity ruleassociated with a virtual resource to be used to implement a networksession on the network, the subset of the configurations comprising anetwork configuration and a second network configuration; determiningthat the network configuration supports a greater number of sessionsthan the second network configuration; and configuring the network basedon the network configuration to support the greater number of sessions,wherein the network configuration assigns at least one instantiation ofa virtual machine (VM) of a first VM type for at least one instantiationof a virtual network function (VNF) of a first VNF type to at least oneserver of a hardware platform of the network.
 9. The method of claim 8,wherein the virtual resource comprises the VM.
 10. The method of claim8, wherein the virtual resource comprises the VNF.
 11. The method ofclaim 8, wherein identifying the plurality of configurations is furtherbased on the plurality of configurations satisfying at least oneconstraint of the network.
 12. The method of claim 11, wherein the atleast one constraint comprises: a virtual computer processing unit(vCPU) allocation for the at least one server; at least one memoryallocation for the at least one server; and at least one networkconnectivity allocation for the at least one server.
 13. The method ofclaim 8, wherein identifying the plurality of configurations comprisesexecuting a formulation of an integer programming problem.
 14. Themethod of claim 13, wherein an objective of the integer programmingproblem is to maximize a number of sessions supported by the network.15. A system comprising: an input/output communicatively coupled to anetwork; a processor; and memory storing instructions that cause theprocessor executing the instructions to effectuate operations, theoperations comprising: identifying a plurality of configurations of thenetwork that satisfies an anti-affinity rule associated with a virtualresource to be used to implement a network session on the network, thesubset of the configurations comprising a network configuration and asecond network configuration; determining that the network configurationsupports a greater number of sessions than the second networkconfiguration; and configuring the network based on the networkconfiguration to support the greater number of sessions, wherein thenetwork configuration assigns at least one instantiation of a virtualmachine (VM) of a first VM type for at least one instantiation of avirtual network function (VNF) of a first VNF type to at least oneserver of a hardware platform of the network.
 16. The system of claim15, wherein the virtual resource comprises the VM.
 17. The system ofclaim 15, wherein identifying the plurality of configurations is furtherbased on the plurality of configurations satisfying at least oneconstraint of the network.
 18. The system of claim 17, wherein the atleast one constraint comprises: a virtual computer processing unit(vCPU) allocation for the at least one server; at least one memoryallocation for the at least one server; and at least one networkconnectivity allocation for the at least one server.
 19. The system ofclaim 15, wherein identifying the plurality of configurations comprisesexecuting a formulation of an integer programming problem.
 20. Thesystem of claim 19, wherein an objective of the integer programmingproblem is to maximize a number of sessions supported by the network.